Efficient query processing in geographic web search engines

TLDR

Geographic web search engines enable region‑constrained queries, a growing area of interest that has attracted major search engines and academic research focused on extracting geographic knowledge, yet query processing remains a bottleneck requiring combined text and spatial techniques. The study investigates efficient query processing in scalable geographic search engines. The authors propose and integrate multiple algorithms into an existing web search query processor, then evaluate their performance on large real datasets and query traces.

Abstract

Geographic web search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called local search, has recently received significant interest from major search engine companies. Academic research in this area has focused primarily on techniques for extracting geographic knowledge from the web. In this paper, we study the problem of efficient query processing in scalable geographic search engines. Query processing is a major bottleneck in standard web search engines, and the main reason for the thousands of machines used by the major engines. Geographic search engine query processing is different in that it requires a combination of text and spatial data processing techniques. We propose several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.